Data suggests that somewhere between 30-40% of marketing campaigns are personalized, most of which only vary content based on the recipient's name. First-name and last-name are simple textual data values that can be leveraged in a limited capacity on a personalized document (e.g., embedded in textual message or in an image). As CRM (customer relations management) systems become more sophisticated, much more data becomes available in which campaigns can be personalized for customers or prospects. The data (e.g. first-name, last-name, age, gender) and logic (a.k.a “business rules”—e.g. “if gender is male and age is less than 30, then special offer=iPhone otherwise special offer=Blackberry) aspects of a variable data publishing (VDP) plan creation are difficult and time consuming.
In some instances, large amounts of data are available for use in creating a VDP plan, but the data is incomplete or lacks context to make it useful and/or easily incorporated into a VDP plan. An example of such data is a large spreadsheet or database wherein at least some of the columns of data do not have a label identifying the column of data, or some of the properties of some of the data is unknown.
There is a need in the art for systems and methods that facilitate utilization of data sources that contain useful information but may be incomplete or lacking context while overcoming the aforementioned deficiencies.